Data anonymisation of vertically partitioned data using Map Reduce techniques on cloud. (2018)

• Record Type: Journal Article
• Authors: Kalidoss, Thangaramya; Sannasi, Ganapathy; Lakshmanan, Sairamesh; Kanagasabai, Kulothungan; Kannan, Arputharaj
• Is Part Of: International journal of communication networks and distributed systems. Volume 20:Number 4(2018)
• Page Start: 519
• Page End: 531
• Publication Date: 2018
• Subjects: data anonymisation -- top-down specialisation -- Map Reduce -- cloud -- privacy preservation; Computer networks -- Periodicals; Telecommunication systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; 004.6
• Languages: English
• ISSNs: 1754-3916

Abstract

Data anonymisation in cloud is used for enhancing the security which is effectively implemented using vertical fragmentation along with encryption and compression techniques. In the existing cloud databases, distributed storage and processing of data are performed by applying fragmentation and search techniques. In order to improve the performance of distributed access plans, Map Reduce techniques can be used which provide fast search and retrieval. Hence, a new distributed security processing mechanism is proposed in this paper to enhance the security of cloud networks which consists of two phases namely encryption and verification phases. For this purpose, a new triple advanced encryption standard algorithm is proposed in this paper that performs secured key distribution based on verification using secured hash algorithm. Moreover, this work uses Map Reduce techniques for fast processing. Experimental results of this work show that our approach provides higher security and effective storage over the existing approaches.